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How would I go about attaching a probability to the prediction outputted by a Gaussian Naive Bayes model ? I'm asking because the predict_proba function U can use with sklearn's Gaussian Naive Bayes classifier only gives me zeros or one, which is not what I want.

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I'm not familiar with sklearn NB methods but it's likely that these are actually the predicted probabilities. NB is known to often assign extreme probabilities, i.e. close to either 0 or 1. This issue implies that the probabilities predicted by NB are not really meaningful, i.e. they cannot (usually) be interpreted as "there is an x % chance that this instance belongs to this class" for example.

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  • $\begingroup$ Thanks for the answer, this is similar to what I read over the last couple of days, the probabilities don't mean much when using Naive Bayes. A possible remedy is to use calibration. link link $\endgroup$ – mmwindel Jun 8 at 6:38

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